code: def make_jets_generator_args(**kwargs):
      defaults = dict(
          generator_type="jets_generator",
          generator_params={
              "idim": 10,
              "odim": 5,
              "adim": 4,
              "aheads": 2,
              "elayers": 1,
              "eunits": 4,
              "dlayers": 1,
              "dunits": 4,
              "positionwise_layer_type": "conv1d",
              "positionwise_conv_kernel_size": 1,
              "use_scaled_pos_enc": True,
              "use_batch_norm": True,
              "encoder_normalize_before": True,
              "decoder_normalize_before": True,
              "encoder_concat_after": False,
              "decoder_concat_after": False,
              "reduction_factor": 1,
              "encoder_type": "transformer",
              "decoder_type": "transformer",
              "transformer_enc_dropout_rate": 0.1,
              "transformer_enc_positional_dropout_rate": 0.1,
              "transformer_enc_attn_dropout_rate": 0.1,
              "transformer_dec_dropout_rate": 0.1,
              "transformer_dec_positional_dropout_rate": 0.1,
              "transformer_dec_attn_dropout_rate": 0.1,
              "conformer_rel_pos_type": "legacy",
              "conformer_pos_enc_layer_type": "rel_pos",
              "conformer_self_attn_layer_type": "rel_selfattn",
              "conformer_activation_type": "swish",
              "use_macaron_style_in_conformer": True,
              "use_cnn_in_conformer": True,
              "zero_triu": False,
              "conformer_enc_kernel_size": 3,
              "conformer_dec_kernel_size": 3,
              "duration_predictor_layers": 2,
              "duration_predictor_chans": 4,
              "duration_predictor_kernel_size": 3,
              "duration_predictor_dropout_rate": 0.1,
              "energy_predictor_layers": 2,
              "energy_predictor_chans": 4,
              "energy_predictor_kernel_size": 3,
              "energy_predictor_dropout": 0.5,
              "energy_embed_kernel_size": 3,
              "energy_embed_dropout": 0.5,
              "stop_gradient_from_energy_predictor": False,
              "pitch_predictor_layers": 2,
              "pitch_predictor_chans": 4,
              "pitch_predictor_kernel_size": 3,
              "pitch_predictor_dropout": 0.5,
              "pitch_embed_kernel_size": 3,
              "pitch_embed_dropout": 0.5,
              "stop_gradient_from_pitch_predictor": False,
              "spks": None,
              "langs": None,
              "spk_embed_dim": None,
              "spk_embed_integration_type": "add",
              "use_gst": False,
              "gst_tokens": 10,
              "gst_heads": 4,
              "gst_conv_layers": 2,
              "gst_conv_chans_list": (3, 3, 6, 6, 12, 12),
              "gst_conv_kernel_size": 3,
              "gst_conv_stride": 2,
              "gst_gru_layers": 1,
              "gst_gru_units": 8,
              "init_type": "xavier_uniform",
              "init_enc_alpha": 1.0,
              "init_dec_alpha": 1.0,
              "use_masking": False,
              "use_weighted_masking": False,
              "segment_size": 4,
              "generator_out_channels": 1,
              "generator_channels": 16,
              "generator_global_channels": -1,
              "generator_kernel_size": 7,
              "generator_upsample_scales": [16, 16],
              "generator_upsample_kernel_sizes": [32, 32],
              "generator_resblock_kernel_sizes": [3, 3],
              "generator_resblock_dilations": [
                  [1, 3],
                  [1, 3],
              ],
              "generator_use_additional_convs": True,
              "generator_bias": True,
              "generator_nonlinear_activation": "LeakyReLU",
              "generator_nonlinear_activation_params": {
                  "negative_slope": 0.1
              },
              "generator_use_weight_norm": True,
          },
      )
      defaults.update(kwargs)
      return defaults
  
file_path: espnet/test/espnet2/gan_tts/jets/test_jets.py
imports: import pytest
  import torch
  from espnet2.gan_tts.jets import JETS
label_desc: Use image node_id 1 for calling a global function with example usage: make_jets_generator_args() and returns: defaults